%0 Conference Proceedings
%T Collecting Valuable Information from Fast Text Streams
%+ Institute of Computing Technology [Beijing] (ICT)
%+ University of Chinese Academy of Sciences [Beijing] (UCAS)
%+ Beijing Lexo Technologies [Beijing]
%A Qi, Baoyuan
%A Ma, Gang
%A Shi, Zhongzhi
%A Wang, Wei
%Z Part 3: Web Mining
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 8th International Conference on Intelligent Information Processing (IIP)
%C Hangzhou, China
%Y Zhongzhi Shi
%Y Zhaohui Wu
%Y David Leake
%Y Uli Sattler
%I Springer
%3 Intelligent Information Processing VII
%V AICT-432
%P 96-105
%8 2014-10-17
%D 2014
%R 10.1007/978-3-662-44980-6_11
%K Fast Text Stream
%K Information Collection
%K Trie
%K N-Gram
%Z Computer Science [cs]Conference papers
%X It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer; secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods.
%G English
%Z TC 12
%2 https://inria.hal.science/hal-01383321/document
%2 https://inria.hal.science/hal-01383321/file/978-3-662-44980-6_11_Chapter.pdf
%L hal-01383321
%U https://inria.hal.science/hal-01383321
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-AICT-432
%~ IFIP-TC12
%~ IFIP-IIP